This study conducts a systematic literature review to examine the applications of artificial intelligence (AI) in agile project management (APM) (AI-in-APM). Guided by the task-technology fit (TTF) lens, it aims to move beyond descriptive summaries and critically analyze the congruence between AI technologies and the tasks of APM.
Mixed methods are employed in this study, which integrates bibliometric analysis of 361 papers on APM with systematic content analysis of 47 papers specifically focused on AI-in-APM.
The analysis maps the fit mechanisms of various AI techniques to core APM tasks and identifies their practical strengths. In addition, it reveals persistent fit gaps and socio-technical tensions (e.g. between algorithmic opacity and agile transparency) that define the future research directions of AI-in-APM.
This study provides an integrative APM framework through the TTF lens. It reveals fit strengths and critical misfits of AI-in-APM.
